Creating 3D image data, such as 3D objects, presents particular challenges both in terms of the complexity of modeling 3D objects and of generating 3D objects to accurately portray real-life objects. Adding to these challenges is the recent application of 3D data to 3D printing, which typically requires full 3D object definition to produce a complete object or product. Current techniques used to create 3D objects or 3D image data include CAD/CAM software products, 3D scanning sensors, and the like. However, these and other 3D modeling techniques often require specific and comprehensive technical expertise, expensive software tools or chains of such tools, or may even require dedicated hardware, such as sensors. These requirements present barriers for the widespread use of 3D modeling.
Currently, there exists techniques for taking 3D data and repairing the data such that the data represents a true volume with a distinct outer shell and interior, capable of being 3D printed. However, these techniques may not output a 3D object that is very refined. For example, a 3D export of map data may generate a visually appealing surface; however, the underlying mesh may be uneven or incomplete. In this example, if the 3D export were printed, it may not stick to the platform or may lean over in away that does not represent the direction of the original topography. In another example, 3D scan data of a person's face may be used to generate a shell or mask. The mask can be made printable, but may not be refined in a way that is appealing, for example, to a user.
Accordingly, there is a need for better and more intuitive techniques for modifying 3D data, for example, for printing and other applications.